Dr.-Ing. Hans Joachim Nern

Dr-Ing H-Joachim Nern obtained his Diploma for Electrical Engineering at the University of Wuppertal, Germany, at the faculty of Electrical Engineering and Information Technology. He received his doctoral degree (Dr-Ing) at the Institute of Automatic Control and Technical Cybernetics at the University of Wuppertal within the research group of Prof Dr sc techn HA Nour Eldin.

The doctoral thesis of Hans-Joachim Nern was related to the application of quaternionic representation schemes to the design of non linear observers. He is specialised in the area of non linear observer design, control theory, pattern recognition, decision making and machine learning techniques, like classification, clustering and case based reasoning.

Since 1994 Dr H-Joachim Nern is engaged in applying AI methods, techniques and algorithms in the field of Information Technology and Knowledge Management: distributed decision support units and recommender systems, multi-agent systems, and collaborative environments (Knixmas, Infrawebs) and platforms. The application of such AI techniques and methods have been verified within several international development projects (RTD) in the fields of e-business, e-logistics, e-marketing, and data-mining as well as customer relationship (CRM) and supply chain management (SCM). Recently he is employed in the following research and development fields: Semantic Web, Ontologies, Web Services, Knowledge Management, Enterprise Application Integration, Enterprise Service Buses, and E-business and E-government applications.

Since 1990 until present he has published up to 100 scientific papers in different interdisciplinary fields like automatic control, pattern recognition, knowledge management, information and media technology, and semantic based systems.

Since 2001 Dr Hans-Joachim Nern is involved in the consulting and expert group Aspasia Knowledge Systems in Duesseldorf.

Since 2004 he is additionally concerned with the TV and media area focused on the merging of TV and IT Know How, methods and techniques.

Abstract: The objective of the presented paper is to give a short overview about watermarking approaches for audio visual objects (AV-objects). Since the market of handling digital media within digital TV stations is strong developing in this paper aspects of innovation-related activities of watermarking applications as well as current research and investigation streams are pointed out. Furthermore an approach for watermarking of AV-objects considering DCT, Wavelet and PLT transforms is discussed.

Abstract: The paper objective is to describe an approach for a software framework consisting of an application oriented tool set for enhanced search, retrieval and processing of audio-visual (AV) content objects. Using semantic web service technologies and watermarking techniques the framework is designed to cover several aspects of object and workflow handling. It allows optimized system integration to support workflow environments realized as P2P as well as open network and mobile service approaches.

"Modules for an Integrated System Approach for Advanced Processing of AV-objects in Digital TV Workflow"

Abstract: The scope of this paper is to describe the integrated system approach for advanced processing of AV-Objects. This system approach is oriented on the design of a software framework consisting of several modules and services, whereas the service designing and composing process is oriented on the WSMO specification. The proposed integrated system approach consists mainly of a threefold approach: meta-search, recognition and classification of objects, application of watermarking methods and the integration of interoperability features of semantic web services. The integrated modules concerning the retrieval, the watermarking, the semantic annotation and the workflow aspects are overviewed.

Abstract:
The paper introduces a system framework, which enables software and Service
providers to generate and establish open and extensible development platforms
for Web Service enabled applications. Within the system design several
non-functional aspects are addressed and covered by applying a set of powerful
(AI-) methodologies: interoperability and adaptability are achieved by
exchanging semantically enriched Services among platform partners within P2P
environments. The machine processability of ontology based structures in
conjunction with "closed loop" approaches in the Service operation,
maintenance and feedback cycle (QoS, full life cycle) ensures implicitly a high
degree of stable adaptability and scalability, as well as the establishment of
extensible platform structures (self-organizing structures). Service
composability is guaranteed by applying open standards. To achieve a
customizable modular development environment “experience” feedback patterns
in distributed rule and case bases (CBR) are archived, evaluated and utilized
within distributed decision making processes.

"Distributed Decision Support Embedded in Semantic Web Service Development and Maintenance Environments for Intelligent e-Business Applications"

Abstract:
The paper introduces an approach for embedding distributed decision support
mechanisms in Semantic Web Service de­velopment environments. To cover several
non-functional aspects, like interoperability, adaptability, Service composability
and scalability a set of AI-methodologies are applied. Interoperability is
achieved by exchanging semantically enriched Services among platform partners
within P2P networks. The machine processability of ontology based struc­tures
in conjunction with "closed loop" approaches in the Service operation,
maintenance and feedback cycle ensures implicitly a high degree of stable
adaptability and scalability. A Quality of Service Broker as part of the
distributed decision support unit evaluates experience feedback patterns
archived in distributed rule and case bases.

Abstract: In this paper the conceptualization and
design of an ICT framework is proposed and discussed - an intelligent framework
for supporting organizational networking and the effective sharing of resources.
The challenges for this are to:
(i) provide a comfortable and "easy to use" but effective
knowledge brokering environment,
(ii) used within a decision supported flexible and highly dynamic
collaboration platform, and
(iii) supplemented with add-ons to fulfil security and privacy
requirements.
These objectives are achieved by developing software components consisting
of:
(i) ontology based and decision supported knowledge management structures
applicable to different entities, and (ii) an interoperability environment
realized as a dynamic and reconfigurable platform using semantic web services and multi
agent systems, (iii) supplemented with semantic web service and agent related privacy
and security modules.
The framework mirrors the modern and future oriented way of
ubiquitous computing, where computers will be relegated to the background of our
lives and everybody may be at the same time client, broker and, provider of services.

Abstract: Due to the fact that nowadays new knowledge creation
and generation is rapidly accelerating, the development of efficient tools and
systems for knowledge management and reasoning is essential. A main application
field in the wide area of knowledge management is designated to decision
support systems - systems which provide comprehensive support in gathering,
organisation, refinement and distribution of knowledge.

The initial point for presenting this paper are the results
of an European project the authors have been involved in [1]. Consequently
and on the basis of this former RTD actions [2, 3, 4] the authors present
in this paper an enhancement of a specific type of decision support methodology -
a new approach in Case Based Reasoning (CBR) for the general application
in WEB-Services. The main realisation trait of this new system is the use of
a closed loop approach considering and taking into account statistically
evaluated user and experience feedback information implicitly.
This closed loop structure assures a stable dynamically growing of the internal
case bases and optimal adaptation to the user resp. systems needs.

Abstract: This paper presents an approach for building research models accessing distributed and heterogene-ous knowledge pools using multi-agent information retrieval. Accordingly task-oriented scenarios for intelli-gent information retrieval are discussed. Searching and browsing activities range from a well-defined search for a specific document to a non-specific task to estimate which kind of information is available. An algorithm for information retrieval is proposed that provides decision support to optimise the search results. The system uses metadata information schemes to provide services in refining user queries to focus a search, in automatically routing queries to relevant servers and in clustering related items.

Abstract:The realisation of a task oriented Decision Support System
(DSS) used within an XPS-based research network is introduced in this paper. The knowledge
(information) retrieval process is instantiated and supervised by a recommender
system - supporting the user resp. researcher in determining and classifying his
information requirements related to his research task. The retrieval procedure is
undertaken stepwise in an iterative way, so that the user is conducted in optimising
his task description and accordingly optimising his information retrieval.

The recommender system provides a multistage access cycle for
converging the searching and retrieval process based on evaluation of feedback
information.
The system extracts out of the user’s (researcher’s) predefined task characteristically
knowledge patterns and accordingly recommends relevant information objects. These objects
are automatically rated with respect to their task related relevancy.